This disclosure relates generally to diagnostic imaging and, more particularly, to an improved method of post processing reconstructed CT images to improve vessel mis-registration and greyscale de-banding between slabs within a CT image.
Typically, in computed tomography (CT) imaging systems, an x-ray source emits a fan or cone-shaped beam toward a subject or object, such as a patient or a piece of luggage. Hereinafter, the terms “subject” and “object” shall include anything capable of being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is typically dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the detector array produces a separate electrical signal indicative of the attenuated beam received by each detector element. The electrical signals are transmitted to a data processing system for analysis which ultimately produces an image.
Generally, the x-ray source and the detector array are rotated about the gantry within an imaging plane and around the subject. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal point. CT detectors typically include a collimator for collimating x-ray beams received at the detector, a scintillator for converting x-rays to light energy adjacent the collimator, and photodiodes for receiving the light energy from the adjacent scintillator and producing electrical signals therefrom. Typically, each scintillator of a scintillator array converts x-rays to light energy. Each scintillator discharges light energy to a photodiode adjacent thereto. Each photodiode detects the light energy and generates a corresponding electrical signal. The outputs of the photodiodes are transmitted to the data processing system for image reconstruction. Imaging data may be obtained using x-rays that are generated at a single polychromatic energy. However, some systems may obtain multi-energy images that provide additional information for generating images.
Cardiac imaging data is obtained by rotating the CT detector about the heart, in either an axial or a helical scan, and obtaining the data during the rotational process. However, many systems (new or legacy) typically do not include a detector that has an axial length that is greater than that of the heart. As such, to obtain full cardiac images, typically several rotations of the detector occur to cover the full axial length of the heart.
Since the introduction of Cardiac CT imaging, the presence of banding artifacts has been one of the limitations of the technology. These artifacts appear as horizontal shifts in multiplanar or 3D images. They can affect all structures in the images, but are most problematic on coronaries as they can show an artificial “rupture” in the vessel. Although the diagnostic remains most the times possible by looking at both “sides” of the vessel individually, the artifacts often create complaints from the customers as it makes vessel visualization and reporting more difficult. Embodiments disclosed allow better visualization and assessment of the vessels, and help the customer create report images where the artifacts are compensated.
In a typical imaging session, cardiac imaging data may be obtained over perhaps 3-4 heartbeats. The number of heartbeats over which data is acquired is dependent on such factors as the axial length of the heart, the axial length of the detector, the rotational speed of the detector about the heart, and the heart rate, as examples. Thus, in an example where data from 3 heartbeats is used to reconstruct an image of the heart, images are thereby reconstructed as separate “slabs”, that are then combined to form the total cardiac image volume. That is, slabs of data are reconstructed wherein each slab is from data within a given heartbeat, and the slabs are joined together along the axial direction to form a complete image volume of the heart. As such, as the detector rotates and the heart continues to beat, imaging data is obtained over a number of heartbeats, and data obtained during each heartbeat is reconstructed into respective images.
However, for a variety of reasons, various types of imaging artifacts can occur. For instance: 1) in-plane and/or slice-to-slice coronary motion can occur within a slab; 2) spatial misalignments can occur at the slab boundary (causing vessels to be mis-registered); and 3) Hounsfield Unit (HU) non-uniformity can occur at the slab boundary as well. That is, between slabs and generally within imaged areas that are removed from the vessel region, greyscale non-uniformity can occur that causes boundaries between slabs to be visible (although such non-uniformity may be merely aesthetic and may not affect a diagnosis, HU non-uniformity correction may nevertheless be applied to minimize or remove the visible boundary between slabs).
Known techniques may be employed to correct the first 1) of the artifacts—in-plane and/or slice-to-slice coronary motion can occur within a slab.
For instance, in one known method in-plane and slice-to-slice motion may be corrected by using filters applied to identified regions of interest to generate a sequence of filtered images. Each of the filtered images in the generated sequence of filtered images includes data acquired near a different reference point, and therefore a motion path corresponding to each region of interest is determined based on one or more correspondences in the sequence of filtered images.
Another known method to correct in-plane and slice-to-slice motion includes reconstructing initial images on which to perform an image correction, and generating an image correction request for the images identified for image correction, with the image correction request specifying a processing operation to be performed on the respective images. The reconstructed initial images are transferred to a separate workstation that automatically initiates the image correction upon verifying a presence of an image correction request on the initial images so as to generate corrected images.
However, image artifacts can include aspects of all three the three artifacts 1)-3). That is, not only can in-plane and/or slice-to-slice coronary motion occur within a slab, but vessel mis-registration can occur at boundaries between slabs due to a number of elements that include but are not limited to inadequate temporal resolution, heartbeat to heartbeat variability, non-repeatable beat-to-beat heart motion, patient motion (patient moving on the table, patient breathing, etc.), and table mis-alignment, as examples. Hounsfield Unit (HU) non-uniformity can occur at the slab boundary as well.
Thus, there is a need to improve vessel mis-registration and greyscale de-banding between slabs within a CT image.